code: def test_multiple_output_files_evaluate_from_args(self):
      data_file = Path(self.FIXTURES_ROOT / "data" / "conll2003.txt")
      paths = []
      out_paths = []
      pred_paths = []
      for i in range(3):
          tmp_path = self.TEST_DIR.joinpath(f"TEST{i}.txt")
  
          # Need to create paths to check when they do not exist
          out_paths.append(tmp_path.parent.joinpath(f"OUTPUTS{i}.json"))
          pred_paths.append(tmp_path.parent.joinpath(f"PREDS{i}.txt"))
  
          copyfile(data_file, tmp_path)
          paths.append(tmp_path)
  
      kebab_args = [
          "evaluate",
          str(
              self.FIXTURES_ROOT
              / "simple_tagger_with_span_f1"
              / "serialization"
              / "model.tar.gz"
          ),
          ",".join(map(str, paths)),
          "--cuda-device",
          "-1",
          "--output-file",
          ",".join(map(str, out_paths)),
          "--predictions-output-file",
          ",".join(map(str, pred_paths)),
      ]
      args = self.parser.parse_args(kebab_args)
      computed_metrics = evaluate_from_args(args)
      computed_by_file = {}
      for k, v in computed_metrics.items():
          fn, *metric_name = k.split("_")
          if fn not in computed_by_file:
              computed_by_file[fn] = {}
          computed_by_file[fn]["_".join(metric_name)] = v
  
      assert len(computed_by_file) == len(paths)
      expected_input_data = data_file.read_text("utf-8")
  
      for i, p in enumerate(paths):
          # Make sure it was not modified
          assert p.read_text("utf-8") == expected_input_data
  
          assert p.stem in computed_by_file, f"paths[{i}]={p.stem}"
  
          assert out_paths[i].exists(), f"paths[{i}]={p.stem}"
          saved_metrics = json.loads(out_paths[i].read_text("utf-8"))
          assert (
              saved_metrics == computed_by_file[p.stem]
          ), f"paths[{i}]={p.stem}"
          assert pred_paths[i].exists(), f"paths[{i}]={p.stem}"
  
imports: import argparse
  import json
  from pathlib import Path
  from typing import Iterator, List, Dict
  from shutil import copyfile
  import pytest
  import torch
  from flaky import flaky
  from allennlp.commands.evaluate import evaluate_from_args, Evaluate
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data.data_loaders import TensorDict
  from allennlp.models import Model
label_desc: Use image node_id 4 for calling the TestEvaluate obj's underlying member method code with example usage: obj.test_multiple_output_files_evaluate_from_args() without return types